Note that the surrogate solvers have their own working directory.
The model is once more coupled_ that reuses 100 time steps as surrogate model. The surrogate model has its own coupled solver with its own predictor, convergence criterion, solver wrappers and models. In addition, a surrogate model is defined, which uses the 1D Python solvers TubeFlow and TubeStructure.īecause of this different discretization, mapping is required. The secant model used is coupled_ where 100 time steps are reused: the previous time steps are used as surrogate model. The coupled solver used is coupled_solvers.iqnism, which has a model and surrogate setting, both of which are a type of model component. The used surrogate model is the combination of the 1D Python solvers TubeFlow and TubeStructure. This is reflected in a different coupled solver and corresponding models, and the type of predictor. This example is identical to the example Fluent2D and Abaqus2D, except for the use of a surrogate model. Tube case with TubeFlow and TubeStructure and Surrogate model Python TubeFlow - Python TubeStructure - Surrogate Python TubeFlow - Python TubeStructure - Analytical
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